What this category of data looks like
Sources of refractory material-related research reports include financial brokerage research reports, fund company industry analysis reports, public documents from refractory material industry associations, and third-party special survey materials. There is no fixed update cycle. Regular industry analysis reports update quarterly or semi-annually. Sudden events such as raw material price fluctuations or production capacity adjustments trigger temporary special reports. Document structures include core performance indicators, raw material composition, production process parameters, market supply and demand data, and investment ratings. Most fields use professional units. For example, refractoriness uses ℃, and compressive strength uses MPa. Single-document word counts vary widely. Some reports with nested tables have higher content density.
Constraints on model access and configuration from these characteristics
Refractory material research reports have dense professional terminology, non-standard units, and strong field correlation. They are also tied to investment decision-making. Model access must adapt to the semantic features of this niche field to avoid generalized recall that reduces investment analysis accuracy. Non-fixed update cycles require configuring incremental sync rules. This ensures the latest special reports are included in the retrieval scope in time, supporting real-time investment judgments. Long documents and high-density table structures require segment configuration that preserves field association integrity. This avoids breaking the contextual logic between indicators and investment conclusions. The need for precise matching of professional parameters requires a similarity threshold higher than general scenarios. This prevents irrelevant research report data from interfering with analysis.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Refractory material research reports contain numerous professional parameter tables with units. Segments that are too long will lose the association between indicators and corresponding investment conclusions. Segments that are too short will damage field integrity. |
topK | Top 6–8 results | Professional indicators in research reports have strong correlation. Too many recalled results will introduce non-core marginal data. Too few will miss supporting content for key performance parameters. |
similarityThreshold | 0.75–0.85 | Semantic matching accuracy for professional terminology has high requirements. A threshold that is too low will introduce irrelevant research reports from non-refractory material categories. A threshold that is too high will miss special reports from niche scenarios. |
PARSE_TIMEOUT_SECONDS | 300 seconds | Some research reports contain multi-layer nested tables. The default parsing timeout cannot complete full content parsing. Extending the timeout ensures normal processing of complex documents. |
MODEL_STREAM_ENABLE | Enabled | Research report retrieval requires real-time return of matching segments. Streaming output reduces user waiting delay and improves interaction fluency. |
PROXY_URL | Fill in the exclusive address provided by the model service provider | Some niche models require requests to be forwarded via a specified proxy. An incorrect proxy address will cause model connection failures. |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: The interface displays the prompt "Model stream response is empty, please check model stream output". Cause: The
MODEL_STREAM_ENABLEconfiguration is not enabled, or the proxy address does not correctly point to the model interface that supports streaming output. Some third-party proxies do not support the streaming format of certain models. - Phenomenon: Adding models such as
qwen3,gpt-4.1 minifails. This issue is common in FastGPT 4.9.2. Cause:MODEL_API_KEYis not filled in correctly, or the exclusive interface path of the model is not adapted. Compatible mode is not enabled when using OneAPI. - Phenomenon: The workflow cannot automatically trigger tool calls, and the model cannot independently choose whether to call tools. Cause: The tool call permission switch is not enabled, and the prompt does not clearly specify the trigger conditions for tool calls. This causes the model to be unable to independently judge the timing of calls.
How to confirm the configuration is complete
- Submit a single refractory material-related research report. Check whether the parsed segments retain core professional indicators and corresponding units, with no field loss or truncation.
- Initiate a search for "Refractory material load softening temperature test standard". Check whether the recalled results include relevant segments of the corresponding professional research report, and whether the similarity meets the configured threshold.
- Call the model interface. Check whether the returned result is streaming output, with no delay, lag, or empty responses.
- Test the tool call function. Initiate a request that requires retrieving research report data. Check whether the model can automatically trigger tool calls and return relevant results.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.